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f7e2ae6 688c130 f7e2ae6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 | """Core KantBench environment implementing the OpenEnv Environment interface."""
from __future__ import annotations
import uuid
from typing import Any, Callable, Optional
from openenv.core.env_server.interfaces import Environment
from env.models import GameAction, GameObservation, GameState, RoundResult
from common.games import GameConfig, get_game, GAMES
from common.strategies import get_strategy, STRATEGIES, OpponentStrategy
from constant_definitions.game_constants import DEFAULT_NUM_ROUNDS
_ONE = int(bool(True))
_ZERO_F = float()
class KantEnvironment(Environment[GameObservation, GameAction, GameState]):
"""Game-theory environment hosting multiple classic games.
The agent plays against a built-in opponent strategy or another agent
function. The opponent's move is computed automatically inside ``step()``
via the selected strategy or the provided ``opponent_fn``.
"""
SUPPORTS_CONCURRENT_SESSIONS = True
def __init__(self) -> None:
super().__init__()
self._game: Optional[GameConfig] = None
self._strategy: Optional[OpponentStrategy] = None
self._strategy_name: str = ""
self._opponent_fn: Optional[Callable[[GameObservation], GameAction]] = None
self._state: GameState = GameState()
# ------------------------------------------------------------------
# OpenEnv interface
# ------------------------------------------------------------------
def reset(
self,
seed: Optional[int] = None,
episode_id: Optional[str] = None,
**kwargs: Any,
) -> GameObservation:
game_name: str = kwargs.get("game", "prisoners_dilemma")
strategy_name: str = kwargs.get("strategy", "tit_for_tat")
num_rounds: Optional[int] = kwargs.get("num_rounds")
opponent_fn: Optional[Callable[[GameObservation], GameAction]] = kwargs.get(
"opponent_fn",
)
self._game = get_game(game_name)
self._opponent_fn = opponent_fn
if opponent_fn is not None:
self._strategy = None
self._strategy_name = "agent"
else:
self._strategy = get_strategy(strategy_name)
self._strategy_name = strategy_name
rounds = num_rounds if num_rounds is not None else self._game.default_rounds
self._state = GameState(
episode_id=episode_id or str(uuid.uuid4()),
game_name=game_name,
opponent_strategy=strategy_name,
total_rounds=rounds,
)
return self._build_observation()
def step(
self,
action: GameAction,
**kwargs: Any,
) -> GameObservation:
if self._game is None:
raise RuntimeError("Call reset() before step().")
if self._state.is_done:
raise RuntimeError("Episode already finished. Call reset().")
if action.action not in self._game.actions:
raise ValueError(
f"Invalid action '{action.action}'. "
f"Choose from: {self._game.actions}"
)
player_action = action.action
opponent_action = self._auto_play_opponent(player_action)
p_pay, o_pay = self._game.payoff_fn(player_action, opponent_action)
new_round = len(self._state.history) + _ONE
result = RoundResult(
round_number=new_round,
player_action=player_action,
opponent_action=opponent_action,
player_payoff=p_pay,
opponent_payoff=o_pay,
)
history = list(self._state.history) + [result]
p_score = self._state.player_score + p_pay
o_score = self._state.opponent_score + o_pay
done = new_round >= self._state.total_rounds
self._state = GameState(
episode_id=self._state.episode_id,
step_count=self._state.step_count + _ONE,
game_name=self._state.game_name,
opponent_strategy=self._state.opponent_strategy,
current_round=new_round,
total_rounds=self._state.total_rounds,
player_score=p_score,
opponent_score=o_score,
history=history,
is_done=done,
)
return self._build_observation(reward=p_pay, last_round=result, done=done)
@property
def state(self) -> GameState:
return self._state
# ------------------------------------------------------------------
# Internal helpers
# ------------------------------------------------------------------
def _auto_play_opponent(self, player_action: str) -> str:
assert self._game is not None
if self._opponent_fn is not None:
opp_obs = self._build_opponent_observation()
opp_action = self._opponent_fn(opp_obs)
opp_actions = self._opponent_actions()
if opp_action.action not in opp_actions:
raise ValueError(
f"Opponent returned invalid action '{opp_action.action}'. "
f"Choose from: {opp_actions}"
)
return opp_action.action
assert self._strategy is not None
hist = [
{
"player_action": r.player_action,
"opponent_action": r.opponent_action,
}
for r in self._state.history
]
opp_actions = self._opponent_actions()
return self._strategy.choose_action(
self._game.game_type, opp_actions, hist,
)
def _opponent_actions(self) -> list[str]:
assert self._game is not None
if self._game.opponent_actions is not None:
return list(self._game.opponent_actions)
gt = self._game.game_type
if gt == "ultimatum":
return ["accept", "reject"]
if gt == "trust":
return _trust_return_actions()
# matrix, public_goods, auction, commons, dictator, centipede,
# stackelberg, and all generated games share action space
return list(self._game.actions)
def _build_opponent_observation(self) -> GameObservation:
"""Build a GameObservation from the opponent's perspective.
Swaps player/opponent in history, scores, and payoffs so the opponent
agent sees itself as the "player".
"""
assert self._game is not None
flipped_history = [
RoundResult(
round_number=r.round_number,
player_action=r.opponent_action,
opponent_action=r.player_action,
player_payoff=r.opponent_payoff,
opponent_payoff=r.player_payoff,
)
for r in self._state.history
]
opp_actions = self._opponent_actions()
return GameObservation(
done=False,
reward=_ZERO_F,
game_name=self._state.game_name,
game_description=self._game.description,
available_actions=opp_actions,
current_round=self._state.current_round,
total_rounds=self._state.total_rounds,
history=flipped_history,
player_score=self._state.opponent_score,
opponent_score=self._state.player_score,
opponent_strategy="agent",
)
def _build_observation(
self,
reward: float = _ZERO_F,
last_round: Optional[RoundResult] = None,
done: bool = False,
) -> GameObservation:
assert self._game is not None
return GameObservation(
done=done,
reward=reward,
game_name=self._state.game_name,
game_description=self._game.description,
available_actions=list(self._game.actions),
current_round=self._state.current_round,
total_rounds=self._state.total_rounds,
history=list(self._state.history),
player_score=self._state.player_score,
opponent_score=self._state.opponent_score,
opponent_strategy=self._strategy_name,
last_round=last_round,
)
def _trust_return_actions() -> list[str]:
from constant_definitions.game_constants import TRUST_ENDOWMENT, TRUST_MULTIPLIER
cap = TRUST_ENDOWMENT * TRUST_MULTIPLIER
return [f"return_{i}" for i in range(cap + _ONE)]
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